Over 35% of lung transplant patients experience acute rejection in the first year and a large majority (perhaps as high as 90%) experience an acute rejection sometime after transplantation. Infection is also an important health issue for immunocompromised lung transplant recipients. The challenge of discriminating infection versus rejection requires a complex and expensive battery of tests including invasive bronchoscopy with biopsy to ensure that the appropriate treatment is given. There is a great need for a sensitive and specific assay that can distinguish rejection from infection in these patients, to allow earlier and more efficacious treatment and to improve long-term outcomes; our proposal aims to develop such an assay. The Central Hypothesis of this work is that the development of low cost DNA sequencing allows for a new, rapid, inexpensive, and non-invasive monitoring test of lung transplant health. This test focuses on the use of cell-free DNA in the blood as a biomarker. With modern genotyping and sequencing approaches, donor-derived cell free DNA (donor DNA or dDNA) may be distinguished from recipient-derived DNA with 99.8% specificity, and elevated dDNA levels correlate well with graft injury. Recent research in heart transplant recipients has shown that dDNA levels rise prior to rejection and can be used to detect the onset of acute rejection earlier than biopsy. We now propose to extend this technology, termed the Genome Transplant Dynamics (GTD) method, to the setting of lung transplantation. In this application, dDNA from the lung will be used to detect rejection (Specific Aim #1) and discriminate rejection from infection (Specific Aim #2). The longitudinal design of the study will also lay the foundation for an assessment of prediction, not just detection, of rejection. We are proposing the following specific aims: (1) Measure the sensitivity and specificity of donor-specific cell-free DNA in the blood of lung transplant patients as a signal for acute rejection, an (2) Demonstrate the specificity of donor-specific cell-free DNA for the differential diagnosis of rejection from infection. We have assembled a distinguished team of investigators to lead this project. Dr. Thomas Snyder, PhD, lead author on the Genome Transplant Dynamics work at Stanford and now chief scientist at ImmuMetrix, will oversee the experimental work and perform the bioinformatics analysis. Dr. Joseph Pilewski, MD, (University of Pittsburgh) and Dr. David Weill, MD, (Stanford University) will provide access to a well-characterized cohort of lung transplant patient samples and will be actively involved in the interpretation of results. Dr. Baba Shahbaba, PhD (University of California, Irvine) will serve as a biostatistics adviser in analyzing the results. This multi-disciplinary team provides all of the required expertise to accomplish the proposed aims.